
==== Front
Poult Sci
Poult Sci
Poultry Science
0032-5791
1525-3171
Elsevier

S0032-5791(24)00809-5
10.1016/j.psj.2024.104230
104230
PROCESSING AND PRODUCT
Metabolomic profiles and compositional differences involved in flavor characteristics of raw breast meat from slow- and fast-growing chickens in Thailand
Indriani Sylvia *
Srisakultiew Nattanan *
Yuliana Nancy Dewi †‡
Yongsawatdigul Jirawat §
Benjakul Soottawat ║
Pongsetkul Jaksuma jaksuma@sut.ac.th
*1
⁎ School of Animal Technology and Innovation, Institute of Agricultural Technology, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand
† Department of Food Science and Technology, Bogor Agricultural University, Bogor 16680, Indonesia
‡ Halal Science Center, IPB University, Bogor 16129, Indonesia
§ School of Food Technology, Institute of Agricultural Technology, Suranaree University of Technology, Nakhon, Ratchasima 30000, Thailand
║ International Center of Excellence in Seafood Science and Innovation, Faculty of Agro-Industry, Prince of Songkla University, Hat Yai, 90110, Thailand
1 Corresponding author: jaksuma@sut.ac.th
23 8 2024
11 2024
23 8 2024
103 11 1042307 6 2024
13 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
This study aimed to differentiate the flavor characteristics of raw chicken breast meat from Thai slow-growing breeds (NC: native chicken, and KC: Korat/crossbred chicken) and fast-growing broilers (BR: broiler chicken) by using NMR-based metabolomic approaches along with multivariate data analysis. Chemical compounds related to chicken's flavor including free amino acids (FAA), ATP and its related compounds, sugars, as well as volatile compounds (VOC), were also investigated. BR had the highest total FAAs, followed by NC and KC (P < 0.05). In contrast, the accumulations of ATP degradation products, particularly ADP and IMP, were found at higher levels in the NC and KC (P < 0.05), while the highest total reducing sugars were noted in the KC (P < 0.05). Most VOCs found in the fresh breasts were products from the degradation of lipids, especially through lipid oxidation, which was found in varied types and proportions among samples. Not only chemical compounds but varying amounts of metabolites among samples were also detected. Apart from 21 identified metabolites, Glu, Gln, and betaine were the most prevalent in all samples with VIP > 1.00. Among 19 metabolic pathways, the most important pathways (P-value < 0.05, FDR < 0.05, impact > 0.05) were discovered to differentiate the flavor of raw chicken breast meat from various breeds. These metabolic pathways included (1) Ala, Asp and Glu metabolism; (2) D-Gln and D-Glu metabolism; (3) Purine metabolism; (4) β-Ala metabolism; (5) Aminoacyl-tRNA biosynthesis; (6) Nicotinate and nicotinamide metabolism; (7) Pyrimidine metabolism. Interestingly, based on the principal component analysis plot and partial least square-discriminant analysis (R2 = 0.9804; Q2 = 0.9782), NC and KC were clustered in the same area and discriminated from BR, indicating their similar flavor characteristics and metabolic profiles. Therefore, the findings could comprehend and distinguish the flavor of chicken breast meat of slow- from fast-growing chicken breeds based on their chemical characteristics and metabolite profiles.

Key words

chicken breed
metabolite
meat quality
flavor
metabolomic
==== Body
pmcINTRODUCTION

Global chicken consumption has seen a remarkable threefold increase over the past decade (Schipmann-Schwarze and Hamm, 2020). Chicken meat accounts for nearly 14% of animal protein consumed by humans and has inadvertently driven consumers’ preference due to its high-protein and low-fat content, aligning with the overall trend towards healthier diets (Connolly et al., 2022). Broilers (BR) and native chickens (NC) are the most popular chicken breeds widely consumed globally (Padhi, 2016; Lee et al., 2017; Mir et al., 2017; Connolly et al., 2022). BR is known as a fast-growing chicken (5–6 wk) that has appealing lean muscle productivity (Choe et al., 2010). While NC has a unique flavor and texture and is healthier, which makes it popular, particularly in Asian countries. For instance, Leung Hang Khao, a Thai NC, possesses a superior nutritional composition with higher insoluble collagen and nucleotides related to umami flavor than BR (Katemala et al., 2022). Nevertheless, the main downside of NC is its slow growth rate (16–20 wk) (Choe et al., 2010; Molee et al., 2018; Katemala et al., 2022). Recently, Korat chicken (KC) has been developed in Thailand for local smallholder farmers by crossbreeding between NC (Leung Hang Khao) sires and BR dams grown at the Suranaree University of Technology (SUT) synthetic line (Promkhun et al., 2023). The growth rate of this alternative crossbreed KC has improved to 10 to 12 wk compared to that of NC, while still maintaining similar meat characteristics and compositions (Poompramun et al., 2021; Maliwan et al., 2022). The higher protein and lower fat content than BR (Katemala et al., 2022; Panpipat et al., 2022), combined with high level of carnosine and low purine content (Katemala et al., 2022; Suwanvichanee et al., 2022), have attracted attention to KC. Due to its novel existence and unique characteristics, KC has gained recent interest in both animal science and food science studies. Recently, Katemala et al. (2022) found that KC has the highest degree of disulfide crosslink and a dominant secondary structure of β-turns and random coils, resulting in exceptional hydrophobicity and unique texture, compared to NC and BR. A former KC serial study focused on the growth performance, as well as basal meat quality/compositions, with or without comparison to NC and BR (Yongsawatdigul et al., 2016; Hang et al., 2018; Katemala et al., 2021; Poompramun et al., 2021; Maliwan et al., 2022; Suwanvichanee et al., 2022; Molee et al., 2022; Pongsetkul et al., 2024). Nevertheless, the available scientific information on the flavor of KC is scarce.

Flavor, which is linked to volatile and nonvolatile compounds, determines consumer acceptance toward food products (Madruga et al., 2009). Amino acids, nucleotides, reducing sugars, fatty acids, and volatiles dominated the flavor development of various meat-derived products (Xiao et al., 2019; Poompramun et al., 2021; Pongsetkul et al., 2022). Metabolomics, particularly 1H-nuclear magnetic resonance (1H-NMR), has been used to accurately and comprehensively understand meat quality components (Yang et al., 2020; Kim et al., 2021). Several studies used 1H-NMR with the multivariate or chemometric analysis to quantify flavor-precursors and other metabolites in beef (Phoemchalard et al., 2022), chicken (Kim et al., 2021), chevon and donkey meat (Akhtar et al., 2021). Korean and Malaysian chicken breeds were distinguished by flavor-active and bioactive compounds using this approach (Kim et al., 2021; Tan et al., 2023). Nevertheless, inadequate studies on the detection of taste- and odor-precursors in Thai slow- and fast-growing chicken breeds using metabolomic-based approach, were found. This study, therefore, investigated the metabolomic profiles of BR, NC, and KC using NMR-based metabolomic approaches coupled with multivariate data analysis. Principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) were used to illustrate all flavor precursors and metabolite correlations. The biochemical pathways involved in the release of odor and taste were also examined. NMR approaches combined with conventional nonvolatile and volatile composition determinations were expected to uncover chicken meats’ unique taste and odor, respectively. This differentiation may contribute to the valorization of native and crossbred chickens in comparison to commercial breeds.

MATERIALS AND METHODS

Sample Collection and Preparation

Three lots of a total of sixty chickens from each breed: (1) commercial broilers ("BR") with an average carcass weight of 2.53 ± 0.58 kg at 6 wk old, (2) Thai native chickens ("NC," Leung-Hang-Khao) with an average carcass weight of 1.45 ± 0.69 kg at 16 wk old, and (3) Korat crossbred chickens ("KC") with an average carcass weight of 1.40 ± 0.37 kg at 12 wk old, were purchased from Charoen Pokphand Foods Public Co., Atchariya Farm, and Betagro Co. (Nakhon Ratchasima, Thailand) between December 2022 and March 2023. The birds were raised in commercial farms certified to follow the standards of the Department of Livestock Development of Thailand, and were slaughtered in the same commercial slaughterhouse (Nakhon Ratchasima, Thailand) under consistent conditions. In brief, the birds were fed ad libitum with a diet containing 21% crude protein during the starter phase (0–3 wk), 19% during the grower phase (4–6 wk), and 17% during the finisher phase (7 wk to slaughter). For the slaughter process, the birds were exsanguinated by stunning with electrocution, followed by a conventional neck cut, bled, and plucked according to Genesis GAP chicken production standards. This approach ensured that the chickens represented the real commercial chickens consumed in Thailand. Then, whole eviscerated carcasses were packed in an ice box, and transported to the laboratory within 1 h. Upon arrival, the carcasses were manually washed and trimmed to obtain the deskinned breast (Pectoralis major), followed by a 24-h postmortem period in a 4°C-chiller. The breast samples were rapidly frozen in liquid nitrogen and stored at −80°C for metabolomics analysis. The remaining samples were stored at −40°C for chemical analysis. All experiments were done within 1 mo.

Determination of Nonvolatile and Volatile Compositions Related to Taste and Odor

Free Amino Acid Compositions

The free amino acid (FAA) profiles of samples were determined following the method of Minh Thuy et al. (2014) with modifications. Samples (10 g) were extracted with 6% (v/v) HClO4, neutralized using 0.1% NaOH, and then filtrated. Subsequently, the filtrates were applied to an amino acid analysis system (Prominence, Shimadzu, Kyoto, Japan), which was equipped with a column (Shim-pack Amino-Li, 100 mm × 6.0 mm i.d., column temperature, 39°C, Shimadzu) and precolumn (Shim-pack ISC-30/S0504 Li, 150 mm × 4.0 mm i.d., Shimadzu). A fluorescence detector (RF-10AXL, Shimadzu) was used to identify the amino acids by expressing them as mg/100 g sample.

Nucleotide-Related Compounds

Nucleotides including adenosine 5’-triphosphate (ATP), adenosine 5’-diphosphate (ADP), adenosine 5’-monophosphate (AMP), inosine 5’-monophosphate (IMP), guanosine 5’-monophosphate (GMP), inosine, hypoxanthine and xanthine were evaluated as per the method of Pongsetkul et al. (2022). The results were calculated and expressed as mg/100 g sample

Sugars

The reducing and phosphorylated sugars including ribose, ribose phosphate, glucose, glucose phosphate, fructose and fructose phosphate were determined. Briefly, samples (5 g) were added with 25 mL of 70% (v/v) CH3OH, homogenized, and then centrifuged to collect the supernatant. The supernatant was then applied to ion exchange chromatography, followed by reductive amination and analysis by the HPCE (Agilent Technologies, Santa Clara) with UV detection to separate, and calculate the amount of each mono- and disaccharide as per the methods of Andersen et al. (2003) and expressed as mg/100 g sample.

Volatile Compounds

Volatile compounds in the samples were characterized by a solid-phase microextraction gas chromatography-mass spectrometry (SPME GC-MS) according to the method of Madruga et al. (2009) with some modifications. Samples (5 g) were added with 10 mL of distilled water, minced, and placed into a 20-mL headspace vial, tightly capped with a PTFE septum. The samples were then heated at 60°C for 2 h. to achieve equilibrium and the volatiles in the extract were allowed to absorb onto an SPME fiber (50/30 lm DVB/Carboxen/PDMS StableFlex) (Supelco, Bellefonte, PA) by heating at 60°C for 1 h. Afterward, the SPME fiber were immediately inserted into the injection port of a GC-MS system. An HP-5890 series II gas chromatography coupled with an HP-5972 mass-selective detector, equipped with a splitless injector, and coupled with a quadrupole mass detector (Hewlett Packard, Atlanta, GA) were used in this study. The volatile compounds were identified using ChemStation Library Search (Wiley 275.L), and comparison with the spectra and retention times of standards were used. The results were expressed as a percentage of the total peak's relative area.

Determination of Metabolomic Profiling Using 1H-NMR

Metabolite Extraction and 1H-NMR Measurement

Proton nuclear magnetic resonance (1H-NMR) was used to determine metabolomic profile of samples according to the method of Xiao et al. (2019) and Phoemchalard et al. (2022) with some modifications. For sample extraction, the frozen breast meat (5 g) was ground using a blender. The powder (100 mg) was resuspended with 600 µL of HPLC-grade water and then vortexed until it dissolved completely. The 400 µL of cold D2O containing 0.1 mM sodium 3-(trimethylsilyl) propionate-2,2,3,3-d4 (TSP) was added as an internal standard. The samples were mixed well and then centrifuged at 15,000 rpm for 5 min, to collect the supernatant. This extraction process was duplicated 2-times, and all supernatants were merged to ensure the complete recovery of the water-soluble extract in the samples. For NMR measurement, the supernatant (500 µL) was transferred to a 5-mm NMR tube (Norwell). Spectra were collected using a 500 MHz Bruker AV III spectrometer equipped with an inverse cryoprobe (CPP BBO 500S1). The initial step of a 2D-1H, 1H-nuclear-overhauled effect spectroscopy (NOESY) pulse sequence was employed to gather 1H-NMR data and to suppress the signal from the solvent. Experiments employed a mixing duration of 100 ms in conjunction with a presaturation of 990 ms (∼80 Hz gammaB1). Spectra were collected at 25°C with a total of 120 scans over a period of 15.0 min.

Metabolite Identification, Quantification, and Pathway Analysis

Chenomx processor (Chenomx Inc., Edmonton, Canada) was used to improve the performance of its peak alignment and baseline normalization. All the spectra were referenced to the internal standard DSS and analyzed against Chenomx Compound Library. The databases of the Human Metabolome Database (HMDB), Kyoto EnFoods cyclopedia of Genes and Genomes (KEGG), Bovine Metabolome Database (BMDB), as well as Biological Magnetic Resonance Data Bank (BMRB) were used. All metabolite concentrations were normalized by weight across all parallel samples before being applied to multivariable analysis.

The statistical analysis of metabolite spectra was carried out using the MetaboAnalyst 5.0 platform (http://www.metaboanalyst.ca/) as per the method of Chong et al. (2019). The partial least squares discriminant analysis (PLS-DA) was employed to decrease data dimensionality, while the performance accuracy was evaluated through leave-one-out cross-validation. The initial assessment of the model fit quality relied on the coefficient of determination (R2) and predictive ability (Q2). The variable importance in the projection (VIP) was measured to discriminate the significance of the metabolites of each sample (a high VIP value (>1) indicates significant metabolite contribution to sample discrimination). For each significant variable of metabolites, 1-way ANOVA and Tukey's range test were performed at a P < 0.05 using SPSS (Version 25, IBM, Armonk, NY). For pathway analysis, the Gallus gallus library in the MetaboAnalyst 5.0 platform was used. Pathways with a P < 0.05 were considered, aligning with the exploratory nature of the study.

Statistical Analysis

Results were presented as means ± SD. One-way analysis of variance (ANOVA) and Tukey's range test was performed to analyze the significant differences among all samples at a significance level of 95% (P < 0.05) using SPSS (Version 25, IBM, Armonk, NY). Moreover, PCA was used to assess the relationship among all volatiles and nonvolatiles related to taste and odor of various chicken breeds using the Unscrambler X multivariate data analysis software (Version 10.1, Camo Analytics, Oslo, Norway).

RESULTS AND DISCUSSION

Free Amino Acid (FAA) Composition

The highest total FAAs were noted in BR (191.74 mg/100 g), followed by NC (181.12 mg/100 g) and KC (172.45 mg/100 g) (P < 0.05) (Table 1). This finding is consistent with Rikimaru and Takahashi (2010), who reported a greater total FAA content in BR compared to the Japanese native Hinai-dori. Diverse genotypic traits or origins of various chicken breeds govern multiple metabolic pathways, thus influencing meat compositions and characteristics (Lengkidworraphiphat et al., 2021; Zheng et al., 2016). Poompramun et al. (2021) reported that BR exhibited a higher residual feed intake (RFI) than indigenous/native chicken breeds, which was associated with a greater accumulation of biochemical compounds in their muscle. A decrease in fractional degrees of degradation, rather than an increase in protein synthesis, promoted the fast-growing chicken breeds to accumulate protein in breast muscle better than native slow-growing chicken (Selle et al., 2023). In addition, the breast meats of NC and KC contained a higher proportion of oxidative muscle fibers, compared to the fast-growing BR (Katemala et al., 2022). These fibers are more prone to oxidation than glycolytic fibers, which may contribute to lower protein or amino acid accumulation in the meat (Ismail and Joo, 2017; Huo et al., 2022). The highest total EAAs was found in BR whereas NC and KC shared a comparable amount (P < 0.05). This result was in line with the findings of Chaiwang et al. (2023), who reported higher EAAs of breast BR compared to the other Thai NC breeds (Mae Hong Son and Pradu Hang Dam). Notably, all chicken breeds contained a similar proportion of FAAs, in which Lys was the predominant EAAs, while Gln, Glu, Asp, Asn, Ala, Gly, and Ser were the predominant NEAAs. These AA proportions were agreed with previous reports (Rikimaru and Takahashi, 2010; Watanabe et al., 2020; Chaiwang et al., 2023). FAAs are generally known as important precursor compounds that contribute to the taste of chicken meat. Glu has been recognized as one of the umami precursors that describes meaty, savory, and broth-like tastes in conjunction with other FAAs and/or nucleotides (Zhang et al., 2017; Chaiwang et al., 2023). Besides, chicken meat flavor could be identified in terms of Val, Ile, Leu, Phe, Arg, and Pro at various proportions, depending on age, diet, and breed (Ali et al., 2019). Interestingly, previous studies have reported higher UAAs in Korean and other Thai NCs, compared to BR (Choe et al., 2010; Chaiwang et al., 2023; Panpipat et al., 2022). However, our results showed comparable total UAAs between BR and NC (81.94–82.60 mg/100 g), overcoming the KC (67.93 mg/100 g) (P < 0.05). In contrast, KC exhibited a high total SAAs (52.39 mg/100 g), which is similar to BR (52.21 mg/100 g) and Korean chicken crossbreeds (51.48 mg/100 g) (Shin et al., 2024). Umami-related compounds, particularly peptides, are zwitterionic, allowing for complexation with other flavor compounds, and leading to the differentiation of taste characteristics (Zhang et al., 2017). The results, therefore, suggest a unique accumulation of AAs in this crossbreed chickens, potentially impacting the distinct characteristics and quality of their meat, compared to either traditional BR or NC breeds.Table 1 Free amino acid (FAA) composition of breast meat from various chicken breeds.

Table 1FAAs (mg/100 g sample)	BR	NC	KC	
Aspartic acid (Asp)	12.13 ± 0.42a	8.99 ± 0.50b	11.99 ± 0.80a	
Asparagine (Asn)	10.05 ± 0.33a	11.03 ± 0.21a	7.13 ± 0.59b	
Glutamic acid (Glu)	19.20 ± 0.32b	21.36 ± 0.91a	18.66 ± 0.59b	
Glutamine (Gln)	40.56 ± 2.60a	41.22 ± 1.15a	30.15 ± 2.23b	
Total umami amino acids (UAA)	81.94 ± 3.05a	82.60 ± 2.14a	67.93 ± 2.98b	
Alanine (Ala)	16.31 ± 0.52b	17.00 ± 0.40b	20.28 ± 0.31a	
Glycine (Gly)	14.42 ± 0.40b	12.09 ± 0.36c	16.06 ± 0.88a	
Proline (Pro)	3.02 ± 0.22a	3.12 ± 0.23a	0.98 ± 0.19b	
Serine (Ser)	11.39 ± 0.80a	12.88 ± 0.59a	9.12 ± 0.44b	
Threonine (Thr)	7.07 ± 0.62a	3.03 ± 0.31c	5.95 ± 0.29b	
Total sweet amino acids (SAA)	52.21 ± 1.44a	48.12 ± 1.38b	52.39 ± 1.90a	
Arginine (Arg)	6.98 ± 0.29b	7.11 ± 0.35b	8.20 ± 0.33a	
Histidine (His)	2.01 ± 0.20a	1.55 ± 0.16b	1.98 ± 0.23a	
Isoleucine (Ile)	3.03 ± 0.15a	2.03 ± 0.22b	0.56 ± 0.13c	
Leucine (Leu)	5.55 ± 0.30a	4.34 ± 0.29b	3.29 ± 0.41c	
Methionine (Met)	2.98 ± 0.44a	3.12 ± 0.19a	1.02 ± 0.21b	
Valine (Val)	4.05 ± 0.32b	3.99 ± 0.27b	5.00 ± 0.28a	
Total bitter amino acids (BAA)	24.60 ± 2.01a	22.14 ± 1.30a	20.05 ± 1.01b	
Cysteine (Cys)	4.44 ± 0.53a	1.01 ± 0.20c	3.06 ± 0.33b	
Lysine (Lys)	10.28 ± 1.01a	6.06 ± 0.58b	11.15 ± 0.52a	
Phenylalanine (Phe)	0.92 ± 0.20b	2.03 ± 0.26a	2.53 ± 0.41a	
Taurine (Tau)	5.05 ± 0.31c	6.13 ± 0.39b	7.77 ± 0.65a	
Tryptophan (Trp)	8.88 ± 0.45a	9.03 ± 0.60a	2.14 ± 0.31b	
Tyrosine (Tyr)	3.42 ± 0.22b	3.00 ± 0.29b	5.43 ± 0.25a	
Total other amino acids (OAA)	32.99 ± 1.46a	27.26 ± 1.58b	32.08 ± 1.40a	
Total FAA	191.74 ± 3.08a	181.12 ± 2.41b	172.45 ± 2.05c	
Total EAA*	44.77 ± 1.73a	36.18 ± 1.96b	33.62 ± 1.94b	
Total NEAA†	119.74 ± 2.97a	118.79 ± 2.60a	111.94 ± 2.59b	
Data are expressed as mean ± standard deviation (n = 3).

BR: Broiler chicken (fast-growing breed).

NC: Thai native chicken (slow-growing breed).

KC: Korat crossbreed chicken (slow-growing crossbreed).

⁎ EAA: Essential amino acids, including His, Ile, Leu, Lys, Met, Phe, Thr, Trp, and Val.

† NEAA: Nonessential amino acids, including Ala, Arg, Asp, Asn, Cys, Gly, Glu, Gln, Pro, Ser, and Tyr.

Different lowercase superscripts in the same row indicate significant differences between samples (P < 0.05).

ATP and Its Related Compounds

Postmortem glycolysis and glycogenolysis govern the rate of ATP degradation thus varying meat qualities, including texture, flavor, water-holding capacity, and other functionalities (Matarneh et al., 2018). According to Table 2, ATP was found only in BR (3.66 mg/100 g), possibly associated with higher ADP and IMP levels in NC and KC (P < 0.05). This suggested a greater extent of ATP degradation via glycolysis after postmortem period in NC and KC, compared to BR. In general, many factors regulate various postmortem changes, such as animal breeds, farming patterns, and slaughtering practices (Mir et al., 2017; Chauhan and England, 2018; Ali et al., 2019). Animal breed is known as one of the factors that affect different rates of postmortem changes, influencing the accumulation of various flavor precursors (Khan et al., 2015). Different breeds of chicken, each possessing distinct muscular tissue properties such as fiber densities and compositions, thereby exhibited variations in glycolysis rates and rigor development of chicken (Mir et al., 2017; Huo et al., 2022). Huo et al. (2022) reported the slow-growing chicken (Xueshan) had higher fiber density and glycolytic potential than the fast-growing chicken (Ross 308), which led to a greater amount of glycogen in Ross 308. A higher glycogen accumulation of slow-growing chicken was consistent with the presence of ATP found only in BR. Glycogen provides an immediate energy source for postmortem ATP production through glycolysis, sustaining ongoing cellular activities, including muscle contraction and enzymatic reactions (Matarneh et al., 2018). ATP degradation products, particularly IMP and GMP, enhance meat's umami taste, particularly by synergizing with L-Glu, thereby boosting palatability as meat flavor intensifies (Indriani et al., 2024). All chicken breeds contained IMP as dominant nucleotides (255.05–289.31 mg/100 g), accounting for 50.78% to 58.25% of total nucleotides, indicating its role as a potent desirable flavor precursor in chicken meat. Notably, IMP was found to be higher in NC and KC than BR (P < 0.05). Similarly, meat from native chicken breeds with more desirable taste was reported to contain higher IMP than that of commercial BR, i.e., indigenous chicken from Japan (Hinai-jidori), Korean (Woorimatdag), and India (Kadaknath) (Rikimaru and Takahashi, 2010; Jayasena et al., 2014; Mir et al., 2017). Muscle development processes and regulatory genes were primarily associated with variations in IMP and GMP concentrations in the meat of various chicken breeds (Katemala et al., 2022). The highest inosine in NC (168.30 mg/100 g) corresponded with a previous report by Katemala et al. (2022). This can be attributed to the higher presence of oxidative fibers (type I fibers) in NC compared to the slow-growing BR (Jaturasitha et al., 2008). Due to their susceptibility to oxidation, these fibers may facilitate the degradation of IMP to inosine through the action of endogenous 5’-nucleotidase (Jaturasitha et al., 2008). Additionally, BR contained the highest amount of hypoxanthine with trace amounts of xanthine (P < 0.05). Meanwhile, NC and KC did not contain xanthine. Although hypoxanthine was reported to have a bitter taste in chicken meat (Shin et al., 2024), it did not generate any taste response in chicken products, particularly cooked meat, due to its low accumulation and high taste thresholds compared to other nucleotides (Xu et al., 2021). Moreover, as purine bases, hypoxanthine can be oxidized into xanthine which subsequently will be converted into uric acid by xanthine oxidase (Aliani et al., 2013). Overall, the results suggested that breed-related factors contribute to various postmortem changes. A greater extent of ATP degradation, resulting in a higher accumulation of its degradation products, was observed in the slow-growing NC and KC breeds. Jaturasitha et al. (2008) described that the lower proportion of muscle fiber type IIB (fast-twitch muscle fibers) in the Thai native chicken (92.8% of total fiber count), compared to fast-growing Bresse chicken (96.1% of total fiber count) resulted in a higher rate of purine nucleotide breakdown during muscle contraction. These intrinsic factors may partially explain the observed variations in nucleotide levels across different breeds, potentially influencing meat flavor as precursor compounds to some extent.Table 2 Nucleotide-related compounds and reducing sugars of breast meat from various chicken breeds.

Table 2Compounds (mg/100 g sample)	BR	NC	KC	
Nucleotides				
 ATP	3.66 ± 0.40	nd.	nd.	
 ADP	39.88 ± 2.25b	70.23 ± 5.16a	65.60 ± 3.44a	
 AMP	10.22 ± 0.60b	10.15 ± 0.49b	30.28 ± 2.55a	
 IMP	255.05 ± 10.25b	280.12 ± 14.14a	289.31 ± 10.20a	
 GMP	24.08 ± 1.01b	20.55 ± 0.49a	20.02 ± 1.02a	
 Inosine	100.02 ± 6.68c	168.30 ± 12.22a	130.15 ± 18.80b	
 Hypoxanthine	4.88 ± 0.45a	2.23 ± 0.40c	3.15 ± 0.36b	
 Xanthine	0.08 ± 0.02	nd.	nd.	
 Total nucleotides	437.87 ± 22.05b	551.58 ± 19.39a	538.51 ± 30.01a	
Reducing sugars				
 Ribose	20.45 ± 2.59c	50.36 ± 4.06b	65.88 ± 4.88a	
 Ribose phosphate	10.13 ± 1.23b	25.02 ± 3.55a	20.13 ± 2.93a	
 Glucose	80.50 ± 9.64	77.33 ± 11.07	78.96 ± 8.99	
 Glucose phosphate	18.22 ± 2.12	20.21 ± 2.00	20.99 ± 3.01	
 Fructose	nd.	20.22 ± 4.10	16.67 ± 2.03	
 Fructose phosphate	13.22 ± 1.01a	10.03 ± 0.65b	11.56 ± 0.77ab	
 Total reducing sugars	142.52 ± 18.88b	203.17 ± 20.03a	214.19 ± 16.01a	
Data are expressed as mean ± standard deviation (n = 3).

nd.: not detected.

BR: Broiler chicken (fast-growing breed).

NC: Thai native chicken (slow-growing breed).

KC: Korat crossbreed chicken (slow-growing crossbreed).

Different lowercase superscripts in the same row indicate significant differences between samples (P < 0.05).

Sugars

Sugars (ribose, glucose, and fructose) and their phosphates are known as one of the flavor precursors of cooked meat as they associate to odor and taste development in meat during cooking, especially by reacting with amino acid via Maillard reaction (Jayasena et al., 2014). Ribose is produced during the breakdown of ATP, with ribose being released as a product alongside hypoxanthine in the later stages of ATP degradation (Ali et al., 2019). Table 2 shows the ribose and ribose phosphate of the slow-growing NC and KC breeds were higher than those in the fast-growing BR chicken (P < 0.05), corresponding well with the greater rates of ATP degradation observed in the slow-growing samples. Aliani and Farmer (2002) reported the concentration of ribose and ribose phosphate in raw fast-growing Ross 308 breast meat was 24.7 mg/100 g and 13.7 mg/100 g, respectively. In fact, small quantities of ribose in raw chicken significantly influence the intensification of flavor, particularly enhancing meaty and roasted notes (Aliani et al., 2013). The highest ribose in KC (65.88 mg/100 g), surpassing that of other breeds in this study and exceeding levels reported in previous studies, could contribute to the dominant characteristic of this alternative crossbred meat, particularly in terms of flavor precursors to create the favorable cooked chicken products. Nevertheless, the various amounts of ribose can be primarily influenced by different genotypes of breeds as well as pre and postmortem metabolism pathways (Aliani et al., 2013). Glucose and its phosphate were found at comparable levels in all chicken breeds, accounting for 77.33 to 80.50 and 18.22 to 20.99 mg/100 g, respectively (P > 0.05). Notably, glucose emerged as the most predominant sugar in chicken breasts regardless of various breeds, agreed with the reports of Aliani et al. (2013), Xiao et al. (2019), and Tan et al. (2023). Most previous studies reported higher glucose levels in BR (Ismail and Joo, 2017; Huo et al., 2022). The larger fiber diameter, along with a higher proportion of fiber type IIB of fast-growing breeds, results in a higher glycolytic potential in the breast muscle, leading to increased glucose accumulation in its meat (Huo et al., 2022). Glucose and glucose-6-phosphate are formed by the glycogenolysis and glycolysis pathways, respectively (Chauhan and England, 2018). However, compared to ribose and its phosphate, these sugars cause much smaller effects on the odor or taste of cooked chicken as reported by Mottram (1998). Fructose was not detected in BR but was found in slow-growing NC and KC, accounting for 20.22 mg/100 g and 16.67 mg/100 g, respectively. Lilyblade and Peterson (1962) reported approximately 11 mg/100 g of fructose in chicken breast muscle, while Aliani and Farmer (2002) found no detectable fructose in breast and leg muscles of 5 commercial chicken meats from the UK. The variations in compositions of reducing sugars were associated to natural genetic variation of chicken breeds (Aliani et al., 2013; Jayasena et al., 2014; Ali et al., 2019). Notably, KC and NC demonstrated higher total reducing sugars than BR (P < 0.05), consistent with previous reports by Jayasena et al. (2014) and Ali et al. (2019), who found that the chicken breast of the slow-growing breed contained higher total reducing sugars than that of commercial broilers. Besides, Poompramun et al. (2021) contemplated that a chicken exhibiting high RFI (such as BR) could store more energy reserve than those of low RFI (such as NC and KC), allowing them to use the reserved energy to respond toward stress via glycogen breakdown. This was reasonable for the existence of ATP with the lowest total nucleotides and reducing sugars in BR (Table 2). Higher glycogen breakdown contributes to increased ATP degradation products, such as IMP, inosine, or ribose, which are responsible for the greater meat intensity observed in slow-growing breeds (Fanatico et al., 2007).

Volatile Compounds

Twenty volatile compounds (VOC) were detected in breast meat from various chicken breeds and classified into 6 groups (alcohol, aldehyde, ketone, hydrocarbon, acid, and ester), as shown in Table 3. All samples exhibited different types and proportions of VOCs, which were reasonable for their unique genotype traits. The presence of VOC in fresh meat, which are associated with the odor emanating from the flesh, can potentially indicate its freshness, helping consumers in their selection when making a purchase. Typically, fresh meat contains low levels and varieties of VOC (Mancinelli et al., 2021), in which many more VOCs will be generated during cooking or processing, influencing the odor and taste of the cooked meat products. In this study, most VOCs found in fresh chicken primarily originated from the degradation of lipids, especially through lipid oxidation. Fatty acids, particularly polyunsaturated fatty acid (PUFA), undergo lipid oxidation generating numerous volatile degradation products after postmortem stages (Mancinelli et al., 2021). Alcohols, including 1-hexanol, 1-octen-3-ol, 1-octanol, and 1-nonanol, were found at certain amounts in all samples. Alcohols, such as 1-octen-3-ol and 1-octanol, are synthesized from the oxidative decomposition of lipids, deriving from linoleic and oleic fatty acids, respectively, or either may originate from the reduction of aldehydes (i.e., hexanal) (Marçal et al., 2022). Ketone was noted as the predominant VOC in all samples (23.34–30.41% of total VOC), governing raw chicken meat odors. Acetoin was found in high amounts in all samples, particularly in the KC, which was higher than in the others (P < 0.05). This compound, responsible for buttery or creamy scent, is often associated with desirable flavor notes in fresh meat. However, in high concentrations, it can sometimes contribute to off-flavors or unpleasant odors, such as a slightly rancid or sour smell (Marçal et al., 2022). Nevertheless, aldehyde constituted the major VOC in raw chicken breast from slow- (Leghorn), medium- (Hubbard and Naked Neck), and fast-growing breeds (Ross 308), as reported by Mancinelli et al. (2021). Among samples, BR and NC contained higher aldehyde content than KC. Mir et al. (2017) noted that aldehyde, particularly nonanal and 2,3-decadienal, contributes to chicken-specific odor and taste. Hexanal was responsible for an unpleasant rancid odor in larger amounts, whereas it gave a pleasant grassy odor in trace amounts (Lorenzo et al., 2014). The absence of hexanal in KC suggested that it had more favorable odor than the others, in terms of grassy odor. Interestingly, Molee et al. (2022) reported that KC had lower amounts of saturated fatty acids (SFA), monounsaturated fatty acids (MUFA), and PUFA than BR. The highest amount of alcohols, ketones, and acids found in the KC in the study, therefore, might be linked to the partial oxidation of those SFA, MUFA, or PUFA. This oxidation process could lead to the release of lipid-derived volatiles, such as alcohols and ketones, which contribute to pleasant odors. A higher level of liver proteins in the slow-growing chicken governed the lipid metabolism and degradation at a greater extent, compared to the fast-growing breed (Zheng et al., 2016). In addition, NC and KC obtained lower amounts of esters, compared to BR. This could be due to the absence of carboxylic-containing compounds, as these compounds are involved in the esterification of medium- and short-chain carboxylic acids with primary and secondary alcohol (Marçal et al., 2022). The various types and amounts of VOCs found in each breed could contribute to the distinct odor characteristics of individuals, which further influence their unique odor and taste profiles in cooked products, as they undergo various compound transformations during cooking. Therefore, VOCs could dictate and distinguish the flavor development in chicken breast meat from various breeds.Table 3 Volatile compounds of breast meat from various chicken breeds.

Table 3Volatiles	Odor description*	Relative peak area of total peak (%)	
		BR	NC	KC	
Alcohols					
1-Hexanol	Sweet, fatty, fruity1	10.12 ± 0.78a	6.59 ± 0.42b	2.84 ± 0.28c	
1-Octen-3-ol	Sweet, earthy1; raw, fishy, oily, fungal, chicken, mushroom, green2	1.35 ± 0.20b	1.08 ± 0.19b	5.03 ± 0.20a	
1-Heptanol	Fragrant, faint, fatty1; leafy, coconut, herbal, peony, chemical, musty, sweet, woody, green2	nd.	5.02 ± 0.32a	0.72 ± 0.16b	
1-Octanol	Sharp fatty-citrus1; burnt, orange, rose, waxy, chemical, metal, mushroom, green2	2.41 ± 0.33c	5.60 ± 0.68b	8.88 ± 0.50a	
2,3-Butanediol	Sweet1	nd.	nd.	4.03 ± 0.51	
1-Nonanol	Rose, floral, fruity1	5.56 ± 0.24a	0.19 ± 0.08c	1.51 ± 0.10b	
Aldehydes					
Nonanal	Fatty, floral, citrus, green1; lime, orange peel, fishy, waxy, fresh, aldehydic, orris, grapefruit2	5.01 ± 0.26a	2.88 ± 0.30c	4.22 ± 0.45b	
Hexanal	Green, grass1	4.60 ± 0.33	5.01 ± 0.30	nd.	
2,3-Decadienal	Citrusy, fatty, chicken1	2.12 ± 0.15b	6.07 ± 0.22a	0.18 ± 0.05c	
Benzaldehyde	Bitter almond1	8.88 ± 0.29a	5.15 ± 0.41b	3.03 ± 0.22c	
Ketones					
2-Heptanone	Fruity, spicy1	10.21 ± 0.70a	3.32 ± 0.23b	nd.	
Acetoin	Buttery, bland, woody, yogurt1	16.68 ± 1.23c	20.02 ± 1.05b	30.41 ± 2.21a	
Hydrocarbons					
Octane	Gasoline1	3.61 ± 0.22b	5.66 ± 0.34a	2.22 ± 0.31c	
1-Octene	NA	7.05 ± 0.25b	10.19 ± 0.60a	7.01 ± 0.41b	
Nonane	Gasoline, sharp1	2.25 ± 0.23c	6.44 ± 0.22a	3.42 ± 0.36b	
Acids					
Octanoic acid	Fatty, mild, unpleasant1	5.02 ± 0.23b	2.20 ± 0.29c	7.40 ± 0.81a	
Nonanoic acid	Fatty, slight, coconut1	6.69 ± 1.01b	5.41 ± 0.22b	10.12 ± 0.71a	
Decanoic acid	Rancid, unpleasant1	nd.	3.05 ± 0.18b	5.16 ± 0.25a	
Esters					
3-Methylbutyl 2-ethylhexanoate	NA	3.11 ± 0.32b	6.12 ± 0.35a	3.82 ± 0.52b	
Methyl octanoate	Fruity, orange, winey1	5.33 ± 0.45	nd.	nd.	
⁎ Flavor description sourced from database available on the web at https://pubchem.ncbi.nlm.nih.gov/1 and Shin et al. (2024).2

NA: not available, data not reported.

nd.: not detected.

BR: Broiler chicken (fast-growing breed).

NC: Thai native chicken (slow-growing breed).

KC: Korat crossbreed chicken (slow-growing crossbreed).

Different lowercase superscripts in the same row indicate significant differences between samples (P < 0.05).

PCA of Chemical Characteristics

The correlation between each chemical characteristic of breast meat and various chicken breeds is presented in Figure 1. Figure 1A shows the score plot of PC1 and PC2 accounting for 54.34% of the total variability. Based on PC1 (36.10%), NC and KC were clustered on the right side, distinct from BR, which was clustered on the left side. Similarly, the slow-growing chicken breeds were discriminated from the fast-growing chicken breeds in terms of their composition of fatty acids and VOCs, as reported by Mancinelli et al. (2021). The correlation loading plot (Figure 1B) indicated the positive correlation between nucleotides (AMP, ADP), sugars (ribose, fructose), Tyr, and VOCs (1-octen-3-ol, 2,3-butanediol, 1-octanol, 1-heptanol, 3-methylbutyl-2-ethylhexanoate, 2,3-decadienal), which were aligned with KC and NC (P < 0.05). In contrast, BR aligned in the negative direction of PC1, which was characterized by high VOCs including 1-nonanol, methyl octanoate, 1-hexanol, benzaldehyde, 2-heptanone, and hexanal. Thus, AMP and ADP could differentiate the umami taste of breast meat from the fast- and slow-growing chicken breeds. Moreover, the positive correlation between these ATP products, free sugars (ribose and fructose), and slow-growing NC and KC suggested a greater extent of ATP degradation via glycolysis and glycogenolysis pathways, leading to the higher accumulation of desirable flavor precursors. These findings aligned with the greater meat intensity observed in slow-growing breeds, compared to the fast-growing BR as reported by Fanatico et al. (2007). Conversely, a positive correlation among Lys, Cys and the BR demonstrated significant flavor precursor compounds of this chicken species. As sulfur-containing amino acids, they are renowned as precursors of volatile aromatic compounds generating meat flavor during heat cooking (Ma et al., 2020). Interestingly, the PCA results suggested that VOCs appeared to be the most significant determinant for distinguishing between chicken breeds (P < 0.05). This could be explained by the varying growing periods of chicken breeds, which subsequently affected their maturity, regulating the dynamic change in the taste of their meat, particularly in terms of volatile compounds (Marçal et al., 2022). Nevertheless, a total variability of nearly 50% could be regarded as the minimum acceptable value for the discrimination among samples (Pallant, 2016). Therefore, it is worth to acclaim that various chicken breeds can be differentiated based on their VOCs as it is influenced by different metabolic patterns.Figure 1 PCA score plot (A) and correlation loading plot (PC1 vs. PC2) (B) at 54.34% total variance among compositions (P > 0.05; black letters, P < 0.05; red letters) related to flavor/taste of breast meat from various chicken breeds.

Figure 1

Metabolomic Profiling Using 1H-NMR

Figure 2 shows a representative 500-MHz 1H-NMR spectra (0.5–8.5 ppm) of breast meat from various chicken breeds. Based on the spectra, 21 primary metabolites were identified including amino acids (Ala, β-Ala, Glu, Gln, Gly, Ile, Thr, Lys, His, Tyr), peptides (anserine, carnosine), amino acid derivatives (betaine, nicotinurate), nucleic acids (AMP, Urd), organic acids (citrate, succinate), and sugars (α-glucose, β-glucose, glycerol) (Table 4). The highest concentration of metabolites was observed in BR (6221.68 ppm) (P < 0.05), whereas NC (5382.38 ppm) and KC (5396.00 ppm) were similar (P > 0.05). The predominant metabolites found in all samples were Gln, Glu, and betaine, with concentrations ranging from 900.33 to 2323.55 ppm, 500.43 to 998.46 ppm, and 598.33 to 1099.26 ppm, respectively. The highest abundances of Gln and Glu were found in BR, compared to others (P < 0.05), suggesting that these 2 UAAs governed the meat flavor of this fast-growing commercial chicken species. Metabolic pathways, particularly during the first 6 wk of feeding, may regulate FAA levels in meat. Chicken muscle energy metabolism postmortem is driven mainly by glycolytic, intermediate, and oxidative pathways, particularly those involving AAs. This includes the release of carnosine and anserine from His via muscle glycolysis (Baldi et al., 2021). Carnosine and its derivative (i.e., anserine) are bioactive endogenous compounds found in vertebrates, functioning as activators of calpain II, myofibrillar ATPase, and phosphorylase, as well as antioxidants (Ali et al., 2019). Interestingly, NC had higher concentrations of these dipeptides than BR and KC (P < 0.05), which was in accordance with Ali et al. (2019) and Charoensin et al. (2021). The higher proportion of white muscle to red muscle tissue of the slow-growing chicken could maintain anaerobic conditions for energy-rich phosphate ester retention (Charoensin et al., 2021). High levels of anserine found in the slow-growing chicken can be attributed to its buffering ability against protons generated by anaerobic glycolysis in various muscle traits (Ali et al., 2019). Indeed, the elevated levels of these bioactive compounds in slow-growing species emphasize their value in the aspects of functional meats (Tan et al., 2023). The crossbred KC demonstrated a higher accumulation of these compounds compared to the commercial BR, thereby contributing to its prominence as a potential choice for functional meat containing bioactive peptides (carnosine and anserine). High concentration of α-glucose was also found in the NC, followed by the KC and BR, respectively (P < 0.05). This could distinguish more desirable flavor of the NC upon cooking from KC and BR, as this reducing sugar can interact with FAAs via the Maillard reaction (Jayasena et al., 2014; Mancinelli et al., 2021; Indriani et al., 2024). Notably, KC could indicate a superior capacity for flavor development through the Maillard reaction due to its higher content of reducing sugars. This information indicates that KC and NC may have more desirable sensory perception than BR after cooking. In general, breast meat from various chicken breeds comprises different compositions of muscle fiber type I (slow-twitch oxidative red fiber), IIA (fast-twitch oxidative-glycolytic white fiber), and IIB (fast-twitch glycolytic white fiber) (Ismail and Joo, 2017; Ma et al., 2020; Huo et al., 2022). This variation could affect metabolite generation through different pathways, leading to distinct meat characteristics, including nutritional value and flavor profile. PCA score and loading plots of the metabolites confirmed the discrimination among chicken breeds by their metabolites, accounting for 53.27% (Supplementary Figure S1). Interestingly, the percentage of total variation of PCA among their metabolites and their chemical characteristics (Figure 1) were equal (∼50%). This suggested a balanced contribution of metabolites and chemical characteristics to the overall variation between the chicken breeds. Moreover, all PCA results indicated the similarity between slow-growing NC and KC, both of which were distinct from the commercial fast-growing BR.Figure 2 Representation of 500-MHz 1H-NMR spectrum (0.5–8.5 ppm) of breast meat from various chicken breeds (21 metabolites).

Figure 2

Table 4 Identified metabolite contents (ppm) of breast meat from various chicken breeds.

Table 4No.	Metabolites	Chemical shifts (ppm) and multiplicity*	BR	NC	KC	
1	Alanine (Ala)	1.46 d, 3.78 q	495.11 ± 23.45a	305.22 ± 39.00b	299.81 ± 20.12b	
2	β-Alanine (β-Ala)	2.56 t, 3.19 t	187.39 ± 10.29ab	183.05 ± 20.16b	200.99 ± 20.23a	
3	AMP	4.01 m, 4.50 q, 4.79 t	8.45 ± 1.05b	7.02 ± 0.94b	180.26 ± 25.22a	
4	Anserine	2.68 m, 3.03 dd	45.02 ± 6.24c	506.03 ± 50.12a	216.20 ± 33.33b	
5	Betaine	3.37 s, 3.93 s	598.33 ± 26.20c	803.23 ± 30.99b	1099.26 ± 56.18a	
6	Carnosine	2.67 m, 303 dd	6.05 ± 0.50c	101.22 ± 10.24a	33.55 ± 2.55b	
7	α-Glucose	3.42 m, 5.23 d	240.30 ± 59.55c	505.23 ± 40.10a	399.36 ± 43.02b	
8	β- Glucose	3.25 m	190.15 ± 19.26	180.20 ± 20.11	203.47 ± 10.60	
9	Glutamate (Glu)	2.34 m, 3.76 dd	998.46 ± 39.25a	500.43 ± 50.12b	608.99 ± 75.43b	
10	Glutamine (Gln)	2.15 m, 3.77 t	2323.55 ± 199.23a	1519.86 ± 100.15b	900.33 ± 60.77c	
11	Glycerol	3.58 m, 3.77 t	88.80 ± 3.33a	10.43 ± 2.10b	5.20 ± 0.45c	
12	Glycine (Gly)	3.55 s	203.19 ± 18.22b	198.23 ± 25.38c	359.66 ± 20.44a	
13	Isoleucine (Ile)	1.02 d, 3.65 d, 2.01 m	60.62 ± 19.24a	42.93 ± 15.15a	6.18 ± 0.38b	
14	Nicotinurate	3.99 s, 7.60 dd, 8.25 d	19.88 ± 0.40c	109.09 ± 2.12a	86.77 ± 2.66b	
15	Succinate	2.04 s	65.22 ± 2.65b	30.67 ± 3.16c	302.99 ± 14.88a	
16	Threonine (Thr)	1.32 d	80.03 ± 10.26a	50.55 ± 4.95b	59.60 ± 5.03b	
17	Lysine (Lys)	1.46 m	156.63 ± 18.22a	38.27 ± 7.78b	170.00 ± 20.31a	
18	Citrate	2.70 d	303.29 ± 40.62a	99.89 ± 10.12b	105.23 ± 15.05b	
19	Histidine (His)	3.23 dd	29.29 ± 1.01a	5.40 ± 0.29c	8.22 ± 0.41b	
20	Uridine (Urd)	4.12 dt	111.95 ± 11.14b	165.32 ± 20.21a	100.01 ± 6.67b	
21	Tyrosine (Tyr)	7.18 m	10.15 ± 0.55c	20.11 ± 1.32b	49.92 ± 5.50a	
Total metabolites	6221.68 ± 200.14a	5382.38 ± 130.21b	5396.00 ± 88.35b	
Data are expressed as mean ± standard deviation (n = 3).

⁎ Multiplicity: s = singlet; d = doublet; t = triplet; q = quartet; dd = doublet of doublets; dt = doublet of triples; m = multiplet.

BR: Broiler chicken (fast-growing breed).

NC: Thai native chicken (slow-growing breed).

KC: Korat crossbreed chicken (slow-growing crossbreed).

Different lowercase superscripts in the same row indicate significant differences between samples (P < 0.05).

To provide a better understanding of the discrimination based on the impacts between spectral data and metabolic pathways, the obtained metabolites were therefore subjected to multivariate analysis by PLS-DA and plotted based on their VIP scores (Figure 3). Based on the PLS-DA analysis, the total variability of 38.89% clearly differentiated the slow- from fast-growing chicken breeds (Figure 3A). The R2 (0.9804) and Q2 (0.9782) values indicated the high reliability of fit-model with good predictability for PLS-DA in various chicken breeds discrimination. PC1 (30.60%) positioned NC and KC on the left side and BR on the right side of the PLS-DA plot, corresponding well with the PCA results based on chemical characteristics or metabolites, albeit accounting for a lower percentage of the total variance. All multivariate analyses confirmed the similar chemical characteristics and metabolites of the slow-growing chicken breeds. Figure 3B demonstrates the most discriminating metabolites among samples which were indicated by VIP score > 1, including AMP, succinate, Gln, anserine, citrate, betaine, carnosine, nicotinurate, Ala, α-glucose, Ile, Glu, Urd, and glycerol. Similarly, lactate, anserine, creatine, carnosine IMP, inosine, and glucose were distinctive biomarkers to distinguish the flavor of breast meat of Chinese native chickens from commercial broilers (Xiao et al., 2021). The highest VIP score (3.80) was observed for AMP allowing it and its related metabolism pathways to discriminate meat characteristics of each chicken breed, particularly in terms of influencing the flavor of the meat. This result agreed with the report of Tan et al. (2023) who stated that ATP degradation products, particularly AMP, can be used effectively for metabolic pattern studies discriminating slow- and fast-growing chicken breeds based on chicken breast muscles. Organic acids, including succinate, citrate, and nicotinurate, exhibited high impacts in differentiating chicken metabolites among each breed, with VIP scores of 2.75, 2.55, and 1.81, respectively. Succinate and citrate are citric acid cycle intermediates involved in various metabolic processes in living organisms, while nicotinurate is responsible for cellular energy production. However, these metabolites primarily support cellular metabolism and energy production rather than directly impacting chicken flavor (Bustin, 2015). The high VIP scores of anserine, betaine, and carnosine (2.60, 2.32, and 1.83, respectively) confirmed that these small peptides are crucial metabolites for differentiation among breeds. While they may not directly impart specific flavor to chicken meat, their functional bioactive properties, such as antioxidant effect or therapeutic effects on hyperuricemia, gout, and Alzheimer's disease (Herculano et al., 2013), which can be claimed to nutritional benefits, underscored their importance in varying levels among chicken breeds. In the aspects of taste, the results revealed that some AAs, which are important flavor precursors, can differentiate chicken among breeds. Those included Glu, Ala, Gln, which are responsible for the umami flavor and provide sweetness (Indriani et al., 2024). This confirmed the presence of various flavor precursor accumulations among samples, which could further impact their meat flavor characteristics differently when cooked or consumed.Figure 3 Partial least squares discriminant analysis (PLS-DA) score plot (R2 = 0.9804, Q2 = 0.9782) (A) and variable importance in projection (VIP) scores (B) of breast meat from various chicken breeds.

Figure 3

Nineteen main metabolic pathways of chicken breast meat affected by various chicken breeds were predicted and identified (Supplementary Table S1). The most important pathways were then determined based on P-value < 0.05, FDR < 0.05, and impact > 0.05, which are summarized in Figure 4. Seven metabolic pathways were closely related to the flavor of chicken breast meat, including (1) Ala, Asp and Glu metabolism; (2) D-Gln and D-Glu metabolism; (3) Purine metabolism; (4) β-Ala metabolism; (5) Aminoacyl-tRNA biosynthesis; (6) Nicotinate and nicotinamide metabolism; (7) Pyrimidine metabolism, which were condensed and outlined as illustrated in Supplementary Figure S2. Ala, Asp and Glu metabolism contributed the most impactful and significant pathways in distinguishing flavor of chicken breast meat. This was reasonable for the abundant concentration of umami-precursor metabolites obtained in this study, particularly Gln and Glu (Table 4). As depicted in Supplementary Figure S2, the Ala, Asp and Glu metabolism governed the release of several intermediate compounds (i.e., L-Glu, L-Gln, L-Asp, L-Ala, and pyruvate) in which subsequently modulated other related metabolic pathways, such as metabolisms of D-amino acids, β-Ala, purine, and pyrimidine, as well as glycolysis/gluconeogenesis. This corresponded well with the subsequent impactful pathways, which were purine, β-Ala, and D-Gln and D-Glu metabolism (Figure 4). Notably, these 3 pathways shared a comparable impact on the generation of metabolites across different chicken breeds. Similar to our results, Ge et al. (2023) found the association between Ala, Asp, Glu metabolism and purine metabolism, in which was related to the breast meat flavor of Beijing You chicken. Purine metabolism involved in the synthesis of AMP metabolite from IMP in which its substrate (L-Gln) was generated from Glu metabolism. The presence of FAAs (such as Asp and Glu) in conjunction with nucleotides associating with purine metabolism govern the synergistic effect on umami flavor development in meat (Ge et al., 2023). A significant abundance of betaine as the major metabolite in all samples could indicate the administration of other minor metabolisms, that is, Gly metabolism via serial methylation reactions (Nyyssölä et al., 2000). Furthermore, β-Ala metabolism resulted in anserine, carnosine, and His, which were found to accumulate in higher quantities, particularly in slow-growing NC and KC, compared to BR (Table 4) establishing them as dominant compounds in these chicken species. The highest Hits-value was accounted for aminoacyl-tRNA biosynthesis (Supplementary Table S1). This corresponded to the accumulation of various amino acid metabolites, as the related amino acid precursors were converted into bioavailable forms by aminoacyl-tRNA synthetase (Supplementary Figure S2). Pyrimidine metabolism, as well as nicotinate and nicotinamide metabolism appeared to be essential pathways in determining metabolic profile of chicken breast meat, although they exhibited less impact compared to the previously mentioned pathways. Uracil was generated via this metabolism thus allowing its conversion to uridine and β-Ala, while nicotinate and nicotinamide metabolism imparted in some quantities of nicotinurate and succinate, which were found at various amounts in each chicken species (Table 4). The various concentrations of metabolites, responsible as flavor precursors for the meat, found in all samples indicated differing rates of metabolic pathways, that were governed by different genotypic traits. From the metabolomic results, main metabolic pathways influencing the flavor of BR, NC, and KC were of Ala, Asp, Glu, D-Gln, D-Glu, purine, and β-Ala metabolism, as well as aminoacyl-tRNA biosynthesis.Figure 4 Pathways topology analysis. The color and size of each circle is based on the P-value and the pathways impact value, respectively. Pathways with a P-value < 0.05, FDR < 0.01, and an impact > 0.05 are labeled.

Figure 4

CONCLUSION

Differences in chemical compounds (both nonvolatiles and volatiles), as well as 1H-NMR metabolomic profiles among chicken breeds, indicated variations in the flavor of their meat. VOCs, particularly those involved in lipid deterioration, were considered the most significant compounds determining the unique flavor of breast meat. PCA plots of chemical compounds and metabolomic profiles, at 54.34 and 53.27% total variability, respectively, differentiated the slow-growing NC and KC from fast-growing BR, indicating the influence of genotypic traits. Alternative crossbred KC, which possesses better growth performance, retained unique flavor characteristics similar to its slow-growing origin breed, NC. Metabolites including ATP degradation products (i.e., AMP), umami AAs (i.e., Glu, Gln, Ala), as well as small functional peptides (i.e. anserine, carnosine, betaine) were considered as the discriminant (VIP > 1). The metabolisms of Ala, Asp, Glu, D-Gln, D-Glu, purine, and β-Ala, as well as aminoacyl-tRNA biosynthesis, were the most distinguishing pathways to determine various chicken breeds. Overall, the varied metabolomic profiles among chicken breeds could comprehend and distinguish the flavor-related metabolites. This information could shed light on the uniqueness or distinct flavor of slow- and fast-growing chicken breeds. However, a sensory evaluation, along with information on changes in metabolites of cooked meat, is suggested for further study to confirm the differentiation in flavor of breast meat as influenced by the various breeds.

DISCLOSURES

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix Supplementary materials

Image, application 1

Image, application 2

Image, application 3

ACKNOWLEDGMENTS

This work was supported by Suranaree University of Technology (SUT). The Center of Scientific and Technological Equipment at Suranaree University of Technology was acknowledged for their sample analysis tools and data analysis. The Center of Excellence on Technology and Innovation for Korat Chicken Business Development was acknowledged for providing samples and offering kind support in this study.

Ethical Approval: All procedures used in the present study were approved by the Ethics Committee on Animal Use of the Suranaree University of Technology (SUT), Thailand (document ID: U1-02631-2559).

Supplementary material associated with this article can be found in the online version at doi:10.1016/j.psj.2024.104230.
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